As a member of the Tealeaves Health team in Roswell, you will be responsible for design, development, testing and support of a highly customizable next generation data platform with data pipelines, tools and frameworks. This individual will work with an existing development team to create the new data platform with latest big data technologies (Spark, Cloud, Cassandra) and migrate the existing prosperity custom data platform and provide production support. The current platform uses a custom built in house ETL process including Perl, Lua, Python, XML, Bash. The candidate will be accountable for understanding the current platform and design, development, implementation and post-implementation maintenance and support of new platform. The duties include data modeling and design, develop and test ETL using python/scala/java jobs on Spark, enhancements/changes to existing code, new data structures, and new reporting capabilities.

The ideal candidate should have extensive knowledge and experience working on building data pipelines, ETL, Rest API with Spark or similar platform using Python/Java. Ideally, this person also should have the knowledge on data architecture, data flows, data analytics, reporting, Business Intelligence. An agile mindset with commitment to teamwork, collaboration, hustle, and strong communication skills are absolute requirements.

Responsibilities:

Work in an Agile Scrum team following process guidelines and participating in team ceremonies.

Analyze, design and code business-related solutions, as well as core architectural changes, using an Agile programming approach resulting in software delivered on time and in budget;

Analyze current data ingestion processes and jobs and its logic into new data Platform.

Acquire data from client or secondary data sources and develop data pipeline to transform, map reduce, analyze data based on business requirements.

Develop Innovate new ways of managing, transforming and validating data

Establish and enforce guidelines to ensure consistency, quality and completeness of data assets